Research and application of automatic mapping method of distribution network protection power supply based on knowledge graph and graph convolution network

This study aims to propose an automatic mapping method for distribution network protection based on knowledge graph (KG) and graph convolution network technology and applies it to power system. The relationship between physical entities in power grid is established by constructing KG, and multisource data fusion and analysis are realized by using graph convolution network technology, so as to realize one-click and automatic mapping of power diagram in power supply places. The distinctiveness of this study lies in the incorporation of KG and deep learning techniques into the field of power supply assurance for distribution networks, achieving automated and digitized generation of power supply assurance device diagrams with real-time dynamic updates capability. This innovation significantly enhances the level of digitization and intelligence in power supply assurance work, injecting new vitality into the field of power supply assurance for distribution networks. This method can provide a digital comprehensive and intuitive presentation for the power supply service and effectively improve the ability to grasp the equipment situation and risk situation awareness.